[bugfix] Upgrade curated environment tf from 2.11 to 2.16 (#3268)

* use tf-2.16

* fix: use shape.as_list() as GPT suggestions

cli/jobs/pipelines-with-components/basics/6a_tf_hello_world/component.yml

@@ -7,7 +7,7 @@ name: tf_hello_world
 display_name: TF-hello-world
 version: 1
 
-environment: azureml://registries/azureml/environments/tensorflow-2.12-cuda11/labels/latest
+environment: azureml://registries/azureml/environments/tensorflow-2.16-cuda11/labels/latest
 command: echo $TF_CONFIG
 resources:
   instance_count: 2

cli/jobs/pipelines/tensorflow-image-segmentation/pipeline.yml

@@ -44,7 +44,7 @@ jobs:
       type: tensorflow
       worker_count: 1 # needs to match instance_count (!)
 
-    environment: azureml://registries/azureml/environments/tensorflow-2.12-cuda11/labels/latest
+    environment: azureml://registries/azureml/environments/tensorflow-2.16-cuda11/labels/latest
     # uncomment below to use custom environment
     # environment:
     #   build: 

cli/jobs/pipelines/tensorflow-image-segmentation/src/tf_helper/training.py

@@ -363,7 +363,7 @@ class TensorflowDistributedModelTrainingSequence:
         self.model = model
 
         params_count = np.sum(
-            [np.prod(v.get_shape()) for v in self.model.trainable_weights]
+            [np.prod(v.shape.as_list()) for v in self.model.trainable_weights]
         )
         self.logger.info(
             "MLFLOW: model_param_count={:.2f} (millions)".format(